class_docstr: DropFeatures() drops a list of variables indicated by the user from the dataframe.
  
  More details in the :ref:`User Guide <drop_features>`.
  
  Parameters
  ----------
  features_to_drop: str or list
      Variable(s) to be dropped from the dataframe
  
  Attributes
  ----------
  features_to_drop_:
      The features that will be dropped.
  
  feature_names_in_:
      List with the names of features seen during `fit`.
  
  n_features_in_:
      The number of features in the train set used in fit.
  
  Methods
  -------
  fit:
      This transformer does not learn any parameter.
  
  fit_transform:
      Fit to data, then transform it.
  
  get_feature_names_out:
      Get output feature names for transformation.
  
  get_support:
      Get a mask, or integer index, of the features selected.
  
  get_params:
      Get parameters for this estimator.
  
  set_params:
      Set the parameters of this estimator.
  
  transform:
      Drops indicated features.
code: def _more_tags(self):
      tags_dict = _return_tags()
      tags_dict["allow_nan"] = True
      # add additional test that fails
      tags_dict["_xfail_checks"][
          "check_parameters_default_constructible"
      ] = "transformer has 1 mandatory parameter"
      tags_dict["_xfail_checks"][
          "check_fit2d_1feature"
      ] = "the transformer raises an error when removing the only column, ok to fail"
      return tags_dict
  
file_path: feature_engine/feature_engine/selection/drop_features.py
imports: from typing import List, Union
  import pandas
  from feature_engine.dataframe_checks import check_X
  from feature_engine.selection.base_selector import BaseSelector
  from feature_engine.tags import _return_tags
label_desc: Use image node_id 3 for calling the DropFeatures obj's underlying member method code with example usage: obj._more_tags() and returns: tags_dict